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README.md

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+# Qwen2.5-Vex-Python
+
+Qwen2.5-Vex-Python is a fine-tuned version of the Qwen2.5-Coder-7B-Instruct model, optimized for enhanced performance in Python code generation and understanding. This model was trained using the Unsloth framework and Hugging Face's TRL library, achieving a training speed twice as fast as conventional methods.
+
+## Model Overview
+
+- **Base Model**: Qwen2.5-Coder-7B-Instruct
+- **Parameter Count**: 7.62 billion
+- **Quantization**: 8-bit (Q8_0)
+- **Architecture**: Qwen2
+- **License**: Apache-2.0
+
+The Qwen2.5 series, developed by Alibaba Cloud's Qwen team, is a collection of large language models designed for various tasks, including code generation. The 7B variant strikes a balance between performance and resource requirements, making it suitable for a wide range of applications. citeturn0search0
+
+## Training Methodology
+
+This model was fine-tuned using the Unsloth framework in conjunction with Hugging Face's TRL (Transformers Reinforcement Learning) library. This combination enabled a training process that was twice as fast as traditional methods, resulting in a more efficient model without compromising performance.
+
+## Usage
+
+To utilize Qwen2.5-Vex-Python for Python code generation or understanding tasks, you can load the model using the Hugging Face Transformers library. Ensure that you have the necessary dependencies installed and that your environment supports 8-bit quantized models.
+
+For detailed instructions on loading and using Qwen2.5 models, refer to the [Qwen Quickstart Guide](https://qwen.readthedocs.io/en/latest/getting_started/quickstart.html). citeturn0search4
+
+## License
+
+This model is licensed under the Apache-2.0 License. You are free to use, modify, and distribute this model, provided that you comply with the terms of the license.
+
+## Acknowledgements
+
+Special thanks to the developers of the Unsloth framework and Hugging Face's TRL library for their contributions to the machine learning community.
+
+For more information on the base model and its capabilities, visit the [Qwen2.5-Coder GitHub repository](https://github.com/QwenLM/Qwen2.5-Coder). citeturn0search0
+
+For a comprehensive overview of the Qwen2.5 series, refer to the [Qwen2.5 Blog Post](https://qwenlm.github.io/blog/qwen2.5/). citeturn0search2 
+
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 base_model: unsloth/qwen2.5-coder-7b-instruct-bnb-4bit
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